Lavapuro, M., Lipponen, A., Artimo, A. & Katko, T. S. 2008: Groundwater sustainability indicators: testing with Finnish data. Boreal Env. Res. 13: 381–402.

The objective of the study was (1) to test the applicability of the groundwater indicators defined by the UNESCO/IAEA/IAH Working Group on Groundwater Indicators at different scales (national/regional/aquifer) by using the data from Finland, and (2) to assess the availability and suitability of data. The indicators allow for assessment of groundwater abundance in proportion to population and water use, as well as its quality and vulnerability. The data used include groundwater recharge estimates, water use and treatment statistics, extent of classified groundwater areas, hydrogeology and groundwater quality (background, chloride and raw water). The indicators show that Finnish groundwater is generally in good shape and of relatively good quality. The groundwater used is renewable and can theoretically be used on a larger scale and enhanced by artificial recharge. The indicators could be more useful in decision-making if focussed on a smaller area, as the relevant decisions concerning groundwater resources are commonly made locally or regionally. Spatial representativeness of samples and data source selection emerged as key considerations.

Suzuki, K., Kodama, Y., Yamazaki, T., Kosugi, K. & Nakai, Y. 2008: Snow accumulation on evergreen needle-leaved and deciduous broad-leaved trees. Boreal Env. Res. 13: 403–416.

We conducted laboratory experiments on the accumulation of snow on the canopies of small evergreen needle-leaved (Picea glehnii) and deciduous broad-leaved (Betula ermanii) trees using an artificial snowfall machine in a cold room. The maximum snow storage was 1.6 to 7.4 mm for Picea glehnii and 1.0 to 3.1 mm for leafless Betula ermanii under a constant snowfall rate of 1 mm h^–1 (water equivalent). The maximum canopy snow storage and the fraction of direct through-fall were parameterized using the plant area index (PAI). We used these parameters in a canopy snow model and estimated the canopy snow storage of a coniferous evergreen needle-leafed forest using this model. The model reproduced the daily canopy snow storage within a relative error of 0.35. A sensitivity analysis using this model showed that the PAI was one of the most important parameters for the estimation of canopy snow storage. Further study is needed on mass release and melt of canopy snow.

Masková, Z., Zemek, F. & Kvet, J. 2008: Normalized difference vegetation index (NDVI) in the management of mountain meadows. Boreal Env. Res. 13: 417–432.

The aim of the study was to test the possibility of using the Normalized Difference Vegetation Index (NDVI) for distinguishing between differently managed mountain grassland sites surrounded by boreal forests. The NDVI was assessed under field conditions in three differently managed meadows (mown, mulched, unmanaged), at an altitude of 1150 to 1170 m in the Bohemian Forest Mts. The mowing and mulching were applied to the respective plots in mid-July and three successive NDVI/aboveground biomass assessments were made before and two after the application of the treatments. The presence of litter, expressed by the green ratio index (GR), strongly affected the reflectance of the grassland canopy. The linear relationships between green biomass and NDVI were statistically significant for all treatments only during the period before the application of the treatments. It was only in the unmanaged plot that a statistically significant linear relationship between NDVI and GR was recorded.

Stenberg, P., Rautiainen, M., Manninen, T., Voipio, P. & Mõttus, M. 2008: Boreal forest leaf area index from optical satellite images: model simulations and empirical analyses using data from central Finland. Boreal Env. Res. 13: 433–443.

A key variable controlling the global carbon, water and energy cycles is the leaf area index (LAI), which thus has an important role in current biosphere-atmosphere research. Several international networks promote the development of remote sensing techniques for global assessment of LAI. We present results from the VALERI (VAlidation of Land European Remote sensing Instruments) network's test site at Hirsikangas in central Finland which represents one of the very few boreal forests in the global networks. In this study, three years of LAI data from Hirsikangas together with medium-resolution satellite images (SPOT HRVIR, Landsat 5 TM and IRS) over the site were used (1) to study the relationships between LAI and different spectral vegetation indices (SVIs), and (2) to test the performance of a physically-based forest reflectance model (PARAS). Simulations with PARAS showed good agreement with empirical data. Results indicated that inclusion of the SWIR band improves the performance of SVIs used for LAI estimation in the boreal forests.

Fältmarsch, R. M., Åström, M. E. & Vuori, K.-M. 2008: Environmental risks of metals mobilised from acid sulphate soils in Finland: a literature review. Boreal Env. Res. 13: 444–456.

The objective of this study was to review the available research information on the environmental risks and effects of metals leached from Finnish acid sulphate soils. The reason for carrying out this study was recent evidence demonstrating that much larger quantities of a number of metals are leached from these soils than from the entire Finnish industry taken together. Alarmingly few scientific studies on the actual biological impacts of acid sulphate soils have been published. However, they all indicate an extensive and serious effect on biota, including metal imbalance in crops and elevated concentrations of Al and Zn in the milk of cows. Acid sulphate soils have also significant, but spatially and temporally variable impacts on biodiversity and community structure of fish, benthic invertebrates and macrophytes, with numerous cases of mass fish kills along the Finnish coast. Furthermore, chronic exposure to high concentrations of metals may pose an actual threat on human health. The potential risks for Alzheimer's and Parkinson's disease in acid sulphate soil landscapes are discussed.

Heikinheimo, O. 2008: Average salinity as an index for environmental forcing on cod recruitment in the Baltic Sea. Boreal Env. Res. 13: 457–464.

Annual average deep-water salinity of the Baltic Sea was found to be usable as an index for environmental forcing that largely determines the level of recruitment of cod (Gadus morhua). Ricker's stock–recruitment equation with annually averaged salinity in the deepest basin of the central Baltic as an environmental factor explained 85% of the interannual variation in the recruitment of cod from 1974–2004 and closely predicted the drastic decrease in recruitment in the 1980s. The reproductive volume index, based on salinity and oxygen concentrations in the reproduction areas, does not provide such a high coefficient of determination. This finding is useful for multispecies modelling of the Baltic fish stocks, and also supports the hypothesis that hydrographic conditions play a dominant role in the recruitment success of cod. The most probable mechanisms are direct effects on the survival of eggs and indirect effects on the early phases of cod via the species composition of the planktonic food organisms.

Karvosenoja, N., Tainio, M., Kupiainen, K., Tuomisto, J. T., Kukkonen, J. & Johansson, M. 2008: Evaluation of the emissions and uncertainties of PM_2.5 originated from vehicular traffic and domestic wood combustion in Finland. Boreal Env. Res. 13: 465–474.

Primary fine particulate matter (PM_2.5) emissions from low-altitude sources, such as traffic and domestic combustion, may cause immediate exposure near the source. In this paper we present emission estimate and uncertainty analysis of PM_2.5 emissions from the vehicular traffic and domestic wood combustion sectors. Our estimate of national PM_2.5 emissions in 2000 from domestic wood combustion was 7.6 Gg a^–1 and that from vehicular traffic, including non-exhaust emissions, 5.8 Gg a^–1. These values correspond to 25% and 19% of the national total PM_2.5 emissions, respectively. The uncertainties were high for non-exhaust traffic and domestic wood combustion emissions, 37% down, 53% up and 36% down, 50% up of the mean value (95% confidence interval limits), respectively. For traffic exhaust emissions, the uncertainties were lower, 11% down, 13% up. Uncertainties in the domestic combustion emission factors were the most important individual parameters accounting for total uncertainty.